Analysis of more than 400,000 women provides case-control evidence for BRCA1 and BRCA2 variant classification.

Clinical genetic testing identifies variants causal for hereditary cancer, information that is used for risk assessment and clinical management. Unfortunately, some variants identified are of uncertain clinical significance (VUS), complicating patient management. Case-control data is one evidence type used to classify VUS, and previous findings indicate that case-control likelihood ratios (LRs) outperform odds ratios for variant classification. As an initiative of the Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) Analytical Working Group we analyzed germline sequencing data of BRCA1 and BRCA2 from 96,691 female breast cancer cases and 303,925 unaffected controls from three studies: the BRIDGES study of the Breast Cancer Association Consortium, the Cancer Risk Estimates Related to Susceptibility consortium, and the UK Biobank. We observed 11,227 BRCA1 and BRCA2 variants, with 6,921 being coding, covering 23.4% of BRCA1 and BRCA2 VUS in ClinVar and 19.2% of ClinVar curated (likely) benign or pathogenic variants. Case-control LR evidence was highly consistent with ClinVar assertions for (likely) benign or pathogenic variants; exhibiting 99.1% sensitivity and 95.4% specificity for BRCA1 and 92.2% sensitivity and 86.6% specificity for BRCA2. This approach provides case-control evidence for 785 unclassified variants, that can serve as a valuable element for clinical classification.

Differences in polygenic score distributions in European ancestry populations: implications for breast cancer risk prediction.

The 313-variant polygenic risk score (PRS313) provides a promising tool for breast cancer risk prediction. However, evaluation of the PRS313 across different European populations which could influence risk estimation has not been performed. Here, we explored the distribution of PRS313 across European populations using genotype data from 94,072 females without breast cancer, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 225,105 female participants from the UK Biobank. The mean PRS313 differed markedly across European countries, being highest in south-eastern Europe and lowest in north-western Europe. Using the overall European PRS313 distribution to categorise individuals leads to overestimation and underestimation of risk in some individuals from south-eastern and north-western countries, respectively. Adjustment for principal components explained most of the observed heterogeneity in mean PRS. Country-specific PRS distributions may be used to calibrate risk categories in individuals from different countries.

Multi-gene panel testing and association analysis in Cypriot breast cancer cases and controls.

Introduction: It is estimated that around 5% of breast cancer cases carry pathogenic variants in established breast cancer susceptibility genes. However, the underlying prevalence and gene-specific population risk estimates in Cyprus are currently unknown. Methods: We performed sequencing on a population-based case-control study of 990 breast cancer cases and 1094 controls from Cyprus using the BRIDGES sequencing panel. Analyses were conducted separately for protein-truncating and rare missense variants. Results: Protein-truncating variants in established breast cancer susceptibility genes were detected in 3.54% of cases and 0.37% of controls. Protein-truncating variants in BRCA2 and ATM were associated with a high risk of breast cancer, whereas PTVs in BRCA1 and PALB2 were associated with a high risk of estrogen receptor (ER)-negative disease. Among participants with a family history of breast cancer, PTVs in ATM, BRCA2, BRCA1, PALB2 and RAD50 were associated with an increased risk of breast cancer. Furthermore, an additional 19.70% of cases and 17.18% of controls had at least one rare missense variant in established breast cancer susceptibility genes. For BRCA1 and PALB2, rare missense variants were associated with an increased risk of overall and triple-negative breast cancer, respectively. Rare missense variants in BRCA1, ATM, CHEK2 and PALB2 domains, were associated with increased risk of disease subtypes. Conclusion: This study provides population-based prevalence and gene-specific risk estimates for protein-truncating and rare missense variants. These results may have important clinical implications for women who undergo genetic testing and be pivotal for a substantial proportion of breast cancer patients in Cyprus.

A likelihood ratio approach for utilizing case-control data in the clinical classification of rare sequence variants: application to BRCA1 and BRCA2.

A large number of variants identified through clinical genetic testing in disease susceptibility genes, are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion), can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analyses of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC), and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity - findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared to classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and pre-formatted excel calculators for implementation of the method for rare variants in BRCA1, BRCA2 and other high-risk genes with known penetrance.

In depth analysis of Cyprus-specific mutations of SARS-CoV-2 strains using computational approaches.

BACKGROUND: This study aims to characterize SARS-CoV-2 mutations which are primarily prevalent in the Cypriot population. Moreover, using computational approaches, we assess whether these mutations are associated with changes in viral virulence. METHODS: We utilize genetic data from 144 sequences of SARS-CoV-2 strains from the Cypriot population obtained between March 2020 and January 2021, as well as all data available from GISAID. We combine this with countries' regional information, such as deaths and cases per million, as well as COVID-19-related public health austerity measure response times. Initial indications of selective advantage of Cyprus-specific mutations are obtained by mutation tracking analysis. This entails calculating specific mutation frequencies within the Cypriot population and comparing these with their prevalence world-wide throughout the course of the pandemic. We further make use of linear regression models to extrapolate additional information that may be missed through standard statistical analysis. RESULTS: We report a single mutation found in the ORF1ab gene (nucleotide position 18,440) that appears to be significantly enriched within the Cypriot population. The amino acid change is denoted as S6059F, which maps to the SARS-CoV-2 NSP14 protein. We further analyse this mutation using regression models to investigate possible associations with increased deaths and cases per million. Moreover, protein structure prediction tools show that the mutation infers a conformational change to the protein that significantly alters its structure when compared to the reference protein. CONCLUSIONS: Investigating Cyprus-specific mutations for SARS-CoV-2 can lead to a better understanding of viral pathogenicity. Researching these mutations can generate potential links between viral-specific mutations and the unique genomics of the Cypriot population. This can not only lead to important findings from which to battle the pandemic on a national level, but also provide insights into viral virulence worldwide.

Multi-omics data integration and network-based analysis drives a multiplex drug repurposing approach to a shortlist of candidate drugs against COVID-19.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is undeniably the most severe global health emergency since the 1918 Influenza outbreak. Depending on its evolutionary trajectory, the virus is expected to establish itself as an endemic infectious respiratory disease exhibiting seasonal flare-ups. Therefore, despite the unprecedented rally to reach a vaccine that can offer widespread immunization, it is equally important to reach effective prevention and treatment regimens for coronavirus disease 2019 (COVID-19). Contributing to this effort, we have curated and analyzed multi-source and multi-omics publicly available data from patients, cell lines and databases in order to fuel a multiplex computational drug repurposing approach. We devised a network-based integration of multi-omic data to prioritize the most important genes related to COVID-19 and subsequently re-rank the identified candidate drugs. Our approach resulted in a highly informed integrated drug shortlist by combining structural diversity filtering along with experts' curation and drug-target mapping on the depicted molecular pathways. In addition to the recently proposed drugs that are already generating promising results such as dexamethasone and remdesivir, our list includes inhibitors of Src tyrosine kinase (bosutinib, dasatinib, cytarabine and saracatinib), which appear to be involved in multiple COVID-19 pathophysiological mechanisms. In addition, we highlight specific immunomodulators and anti-inflammatory drugs like dactolisib and methotrexate and inhibitors of histone deacetylase like hydroquinone and vorinostat with potential beneficial effects in their mechanisms of action. Overall, this multiplex drug repurposing approach, developed and utilized herein specifically for SARS-CoV-2, can offer a rapid mapping and drug prioritization against any pathogen-related disease.

Performance evaluation of pipelines for mapping, variant calling and interval padding, for the analysis of NGS germline panels.

BACKGROUND: Next-generation sequencing (NGS) represents a significant advancement in clinical genetics. However, its use creates several technical, data interpretation and management challenges. It is essential to follow a consistent data analysis pipeline to achieve the highest possible accuracy and avoid false variant calls. Herein, we aimed to compare the performance of twenty-eight combinations of NGS data analysis pipeline compartments, including short-read mapping (BWA-MEM, Bowtie2, Stampy), variant calling (GATK-HaplotypeCaller, GATK-UnifiedGenotyper, SAMtools) and interval padding (null, 50 bp, 100 bp) methods, along with a commercially available pipeline (BWA Enrichment, Illumina®). Fourteen germline DNA samples from breast cancer patients were sequenced using a targeted NGS panel approach and subjected to data analysis. RESULTS: We highlight that interval padding is required for the accurate detection of intronic variants including spliceogenic pathogenic variants (PVs). In addition, using nearly default parameters, the BWA Enrichment algorithm, failed to detect these spliceogenic PVs and a missense PV in the TP53 gene. We also recommend the BWA-MEM algorithm for sequence alignment, whereas variant calling should be performed using a combination of variant calling algorithms; GATK-HaplotypeCaller and SAMtools for the accurate detection of insertions/deletions and GATK-UnifiedGenotyper for the efficient detection of single nucleotide variant calls. CONCLUSIONS: These findings have important implications towards the identification of clinically actionable variants through panel testing in a clinical laboratory setting, when dedicated bioinformatics personnel might not always be available. The results also reveal the necessity of improving the existing tools and/or at the same time developing new pipelines to generate more reliable and more consistent data.

Generalized linear models provide a measure of virulence for specific mutations in SARS-CoV-2 strains.

This study aims to highlight SARS-COV-2 mutations which are associated with increased or decreased viral virulence. We utilize genetic data from all strains available from GISAID and countries' regional information, such as deaths and cases per million, as well as COVID-19-related public health austerity measure response times. Initial indications of selective advantage of specific mutations can be obtained from calculating their frequencies across viral strains. By applying modelling approaches, we provide additional information that is not evident from standard statistics or mutation frequencies alone. We therefore, propose a more precise way of selecting informative mutations. We highlight two interesting mutations found in genes N (P13L) and ORF3a (Q57H). The former appears to be significantly associated with decreased deaths and cases per million according to our models, while the latter shows an opposing association with decreased deaths and increased cases per million. Moreover, protein structure prediction tools show that the mutations infer conformational changes to the protein that significantly alter its structure when compared to the reference protein.

NGS Panel Testing of Triple-Negative Breast Cancer Patients in Cyprus: A Study of BRCA-Negative Cases.

In Cyprus, approximately 9% of triple-negative (estrogen receptor-negative, progesterone receptor-negative, and human epidermal growth factor receptor 2-negative) breast cancer (TNBC) patients are positive for germline pathogenic variants (PVs) in BRCA1/2. However, the contribution of other genes has not yet been determined. To this end, we aimed to investigate the prevalence of germline PVs in BRCA1/2-negative TNBC patients in Cyprus, unselected for family history of cancer or age of diagnosis. A comprehensive 94-cancer-gene panel was implemented for 163 germline DNA samples, extracted from the peripheral blood of TNBC patients. Identified variants of uncertain clinical significance were evaluated, using extensive in silico investigation. Eight PVs (4.9%) were identified in two high-penetrance TNBC susceptibility genes. Of these, seven occurred in PALB2 (87.5%) and one occurred in TP53 (12.5%). Interestingly, 50% of the patients carrying PVs were diagnosed over the age of 60 years. The frequency of non-BRCA PVs (4.9%) and especially PALB2 PVs (4.3%) in TNBC patients in Cyprus appears to be higher compared to other populations. Based on these results, we believe that PALB2 and TP53 along with BRCA1/2 genetic testing could be beneficial for a large proportion of TNBC patients in Cyprus, irrespective of their age of diagnosis.

Alport syndrome: Proteomic analysis identifies early molecular pathway alterations in Col4a3 knock out mice.

AIM: Alport syndrome (AS) is the second most common hereditary kidney disease caused by mutations in collagen IV genes. Patients present with microhaematuria that progressively leads to proteinuria and end stage renal disease. Currently, no specific treatment exists for AS. Using mass spectrometry based proteomics, we aimed to detect early alterations in molecular pathways implicated in AS before the stage of overt proteinuria, which could be amenable to therapeutic intervention. METHODS: Kidneys were harvested from male Col4a3-/- knock out and sex and age-matched Col4a3+/+ wild-type mice at 4 weeks of age. Purified peptides were separated by liquid chromatography and analysed by high resolution mass spectrometry. The Cytoscape bioinformatics tool was used for function enrichment and pathway analysis. PPARα expression levels were evaluated by immunofluorescence and immunoblotting. RESULTS: Proteomic analysis identified 415 significantly differentially expressed proteins, which were mainly involved in metabolic and cellular processes, the extracellular matrix, binding and catalytic activity. Pathway enrichment analysis revealed among others, downregulation of the proteasome and PPAR pathways. PPARα protein expression levels were observed to be downregulated in Alport mice, supporting further the results of the discovery proteomics. CONCLUSION: This study provides additional evidence that alterations in proteins which participate in cellular metabolism and mitochondrial homeostasis in kidney cells are early events in the development of chronic kidney disease in AS. Of note is the dysregulation of the PPAR pathway, which is amenable to therapeutic intervention and provides a new potential target for therapy in AS.

Rapid and Sensitive Assessment of Globin Chains for Gene and Cell Therapy of Hemoglobinopathies.

The ß-hemoglobinopathies sickle cell anemia and ß-thalassemia are the focus of many gene-therapy studies. A key disease parameter is the abundance of globin chains because it indicates the level of anemia, likely toxicity of excess or aberrant globins, and therapeutic potential of induced or exogenous ß-like globins. Reversed-phase high-performance liquid chromatography (HPLC) allows versatile and inexpensive globin quantification, but commonly applied protocols suffer from long run times, high sample requirements, or inability to separate murine from human ß-globin chains. The latter point is problematic for in vivo studies with gene-addition vectors in murine disease models and mouse/human chimeras. This study demonstrates HPLC-based measurements of globin expression (1) after differentiation of the commonly applied human umbilical cord blood-derived erythroid progenitor-2 cell line, (2) in erythroid progeny of CD34+ cells for the analysis of clustered regularly interspaced short palindromic repeats/Cas9-mediated disruption of the globin regulator BCL11A, and (3) of transgenic mice holding the human ß-globin locus. At run times of 8 min for separation of murine and human ß-globin chains as well as of human γ-globin chains, and with routine measurement of globin-chain ratios for 12 nL of blood (tested for down to 0.75 nL) or of 300,000 in vitro differentiated cells, the methods presented here and any variant-specific adaptations thereof will greatly facilitate evaluation of novel therapy applications for ß-hemoglobinopathies.